With the advent of high-power pulsed lasers, laser peening has emerged as a new and very promising technique to improve the resistance properties of materials to fatigue, wear and corrosion. In this paper, the effect of laser peening on the surface performance of QT700-2 materials was investigated, the parameters of laser peening were optimized by an artificial neural network (ANN) method. A series of experiments was carried out by using a high-power, Q-Switched, pulsed neodymium-glass laser. The microstructure features were analyzed with SEM and the hardness and residual stresses at the surface and in-depth were measured. The results indicate that the depth of hardened layer was about 0.31ı1.40mm for a different shot number of 1-4 times and the compressive residual stress at the surface increases with increasing laser pulse energy, from -165MPa for the low energy 12J to -410MPa for the higher energy 20J. Laser peening can restrain nucleation of fatigue cracks and improve the fatigue life of nodular cast iron materials.